/*
 *    WaveformGeneratorDrift.java
 *    Copyright (C) 2008 University of Waikato, Hamilton, New Zealand
 *    @author Albert Bifet
 *
 *    This program is free software; you can redistribute it and/or modify
 *    it under the terms of the GNU General Public License as published by
 *    the Free Software Foundation; either version 2 of the License, or
 *    (at your option) any later version.
 *
 *    This program is distributed in the hope that it will be useful,
 *    but WITHOUT ANY WARRANTY; without even the implied warranty of
 *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *    GNU General Public License for more details.
 *
 *    You should have received a copy of the GNU General Public License
 *    along with this program; if not, write to the Free Software
 *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */
package moa.streams.generators;

import weka.core.DenseInstance;
import weka.core.Instance;

import moa.core.InstancesHeader;
import moa.core.ObjectRepository;
import moa.options.IntOption;
import moa.tasks.TaskMonitor;

public class WaveformGeneratorDrift extends WaveformGenerator {

	private static final long serialVersionUID = 1L;

	public IntOption numberAttributesDriftOption = new IntOption("numberAttributesDrift",
			'd', "Number of attributes with drift.", 0, 0, TOTAL_ATTRIBUTES_INCLUDING_NOISE);

	protected int[] numberAttribute;

	@Override
	public String getPurposeString() {
		return "Generates a problem of predicting one of three waveform types with drift.";
	}

	@Override
	protected void prepareForUseImpl(TaskMonitor monitor,
			ObjectRepository repository) {
		super.prepareForUseImpl(monitor,repository);
		int numAtts = this.addNoiseOption.isSet() ? TOTAL_ATTRIBUTES_INCLUDING_NOISE
				: NUM_BASE_ATTRIBUTES;
		this.numberAttribute = new int[numAtts];
		for (int i = 0; i < numAtts; i++) {
			this.numberAttribute[i] = i;
		}
		//Change atributes
		int randomInt = this.instanceRandom.nextInt(numAtts);
		int offset = this.instanceRandom.nextInt(numAtts);
		for (int i = 0; i < this.numberAttributesDriftOption.getValue(); i++) {
			this.numberAttribute[(i + randomInt) % numAtts] = (i + offset) % numAtts;
			this.numberAttribute[(i + offset) % numAtts] = (i + randomInt) % numAtts;
		}
	}

	@Override
	public Instance nextInstance() {
		InstancesHeader header = getHeader();
		Instance inst = new DenseInstance(header.numAttributes());
		inst.setDataset(header);
		int waveform = this.instanceRandom.nextInt(NUM_CLASSES);
		int choiceA = 0, choiceB = 0;
		switch (waveform) {
		case 0:
			choiceA = 0;
			choiceB = 1;
			break;
		case 1:
			choiceA = 0;
			choiceB = 2;
			break;
		case 2:
			choiceA = 1;
			choiceB = 2;
			break;

		}
		double multiplierA = this.instanceRandom.nextDouble();
		double multiplierB = 1.0 - multiplierA;
		for (int i = 0; i < NUM_BASE_ATTRIBUTES; i++) {
			inst.setValue(this.numberAttribute[i], (multiplierA * hFunctions[choiceA][i])
					+ (multiplierB * hFunctions[choiceB][i])
					+ this.instanceRandom.nextGaussian());
		}
		if (this.addNoiseOption.isSet()) {
			for (int i = NUM_BASE_ATTRIBUTES; i < TOTAL_ATTRIBUTES_INCLUDING_NOISE; i++) {
				inst.setValue(this.numberAttribute[i], this.instanceRandom.nextGaussian());
			}
		}
		inst.setClassValue(waveform);
		return inst;
	}

	@Override
	public void getDescription(StringBuilder sb, int indent) {
		// TODO Auto-generated method stub

	}

}
